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Praneeth Netrapalli
Praneeth Netrapalli
Подтвержден адрес электронной почты в домене google.com - Главная страница
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Процитировано
Процитировано
Год
Low-rank matrix completion using alternating minimization
P Jain, P Netrapalli, S Sanghavi
Proceedings of the forty-fifth annual ACM symposium on Theory of computing …, 2013
10622013
How to escape saddle points efficiently
C Jin, R Ge, P Netrapalli, SM Kakade, MI Jordan
International Conference on Machine Learning, 1724-1732, 2017
6902017
Phase retrieval using alternating minimization
P Netrapalli, P Jain, S Sanghavi
Advances in Neural Information Processing Systems 26, 2013
6142013
Non-convex robust PCA
P Netrapalli, N UN, S Sanghavi, A Anandkumar, P Jain
Advances in Neural Information Processing Systems 27, 2014
3082014
Morel: Model-based offline reinforcement learning
R Kidambi, A Rajeswaran, P Netrapalli, T Joachims
Advances in neural information processing systems 33, 21810-21823, 2020
2522020
What is local optimality in nonconvex-nonconcave minimax optimization?
C Jin, P Netrapalli, M Jordan
International conference on machine learning, 4880-4889, 2020
245*2020
Accelerated gradient descent escapes saddle points faster than gradient descent
C Jin, P Netrapalli, MI Jordan
Conference On Learning Theory, 1042-1085, 2018
2172018
Learning the graph of epidemic cascades
P Netrapalli, S Sanghavi
ACM SIGMETRICS Performance Evaluation Review 40 (1), 211-222, 2012
2052012
Learning sparsely used overcomplete dictionaries via alternating minimization
A Agarwal, A Anandkumar, P Jain, P Netrapalli
SIAM Journal on Optimization 26 (4), 2775-2799, 2016
1702016
Parallelizing stochastic gradient descent for least squares regression: mini-batching, averaging, and model misspecification
P Jain, S Kakade, R Kidambi, P Netrapalli, A Sidford
Journal of Machine Learning Research 18, 2018
142*2018
Information-theoretic thresholds for community detection in sparse networks
J Banks, C Moore, J Neeman, P Netrapalli
Conference on Learning Theory, 383-416, 2016
136*2016
On nonconvex optimization for machine learning: Gradients, stochasticity, and saddle points
C Jin, P Netrapalli, R Ge, SM Kakade, MI Jordan
Journal of the ACM (JACM) 68 (2), 1-29, 2021
135*2021
Efficient algorithms for smooth minimax optimization
KK Thekumparampil, P Jain, P Netrapalli, S Oh
Advances in Neural Information Processing Systems 32, 2019
1292019
Streaming pca: Matching matrix bernstein and near-optimal finite sample guarantees for oja’s algorithm
P Jain, C Jin, SM Kakade, P Netrapalli, A Sidford
Conference on learning theory, 1147-1164, 2016
1242016
Learning sparsely used overcomplete dictionaries
A Agarwal, A Anandkumar, P Jain, P Netrapalli, R Tandon
Conference on Learning Theory, 123-137, 2014
1132014
Faster eigenvector computation via shift-and-invert preconditioning
D Garber, E Hazan, C Jin, C Musco, P Netrapalli, A Sidford
International Conference on Machine Learning, 2626-2634, 2016
110*2016
The pitfalls of simplicity bias in neural networks
H Shah, K Tamuly, A Raghunathan, P Jain, P Netrapalli
Advances in Neural Information Processing Systems 33, 9573-9585, 2020
1022020
Fast exact matrix completion with finite samples
P Jain, P Netrapalli
Conference on Learning Theory, 1007-1034, 2015
982015
The step decay schedule: A near optimal, geometrically decaying learning rate procedure for least squares
R Ge, SM Kakade, R Kidambi, P Netrapalli
Advances in Neural Information Processing Systems 32, 2019
97*2019
Provable efficient online matrix completion via non-convex stochastic gradient descent
C Jin, SM Kakade, P Netrapalli
Advances in Neural Information Processing Systems 29, 2016
922016
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